Quality Manager, Six Sigma Green Belt, and GMP

In the first step, this course provides professional knowledge in the application of the ISO DIN EN 9001 standard as well as in the planning, introduction, maintenance and effectiveness control of a QM system in order to formulate corporate goals, optimize processes and ensure product quality in the long term. You will then learn how to use the Six Sigma management system, from the basics to the implementation of more complex Six Sigma projects in your company. Finally, the subject of Good Manufacturing Practice (GMP) is dealt with in particular - guidelines for quality assurance of production processes and environments, for example in the pharmaceutical industry, but also in the production of cosmetics, food and animal feed are described here. You will also learn how artificial intelligence (AI) is used in your professional environment.
  • Certificates: Certificate "Quality representative with TÜV Rheinland-certified qualification"
    "Six Sigma Green Belt" Certificate
    GMP - Good Manufacturing Practice" certificate
  • Examination: Praxisbezogene Projektarbeiten mit Abschlusspräsentationen
    Qualitätsbeauftragte:r mit TÜV Rheinland geprüfter Qualifikation
    Six Sigma Green Belt
  • Teaching Times: Full-time
    Monday to Friday from 8:30 a.m. to 3:35 p.m. (in weeks with public holidays from 8:30 a.m. to 5:10 p.m.)
  • Language of Instruction: German
  • Duration: 12 Weeks

Quality officers with TÜV Rheinland-certified qualifications

Basics of quality management (approx. 1 day)

Terms and definitions

Quality management

Quality management systems

Standards and guidelines


Process basics (approx. 1 day)

What is a process?

Process management according to ISO 9001

Identification of processes

ISO 9001 process model


Corporate environment (approx. 1 day)

Context of the organization

Interested parties

Scope of application


Management (approx. 1.5 days)

Commitment to the QM system

Quality policy

Responsibilities and powers


Planning (approx. 1 day)

Dealing with risks and opportunities

Quality objectives and planning

Planning changes


Artificial intelligence (AI) in the work process

Presentation of specific AI technologies

and possible applications in the professional environment


Support (approx. 2 days)

Resources

Competence

Awareness

Communication

Knowledge of the organization, knowledge management

Documentation of the quality management system


Operation (approx. 2 days)

Operational planning

Requirements for products and services

Product development

Predictive failure avoidance with FMEA, QFD, Poka Yoke

External provision

Supply Chain Act (LkSG) and EU Sustainability Directive (CSDDD)

Production and service provision

Release of products and services

Control of non-conforming results


Evaluation of performance (approx. 1.5 days)

Monitoring and measurement

Internal audit

Management review


Improvement (approx. 1 day)

Non-conformity and corrective actions

Continuous improvement


Auditing and certification (approx. 1.5 days)

Fundamentals of auditing

Internal audits

Audit procedure

Auditing external providers or external parties

Certification audit


Communication (approx. 2 days)

Building blocks of communication

The iceberg principle of communication

The four-ears model

Communication behavior in audits


Project management (approx. 1 day)

Definition of project

Managing projects successfully


Total Quality Management (approx. 0.5 days)

Quality of an organization

ISO 9004: Guidance for achieving sustainable success

EFQM Model for Excellence


Project work, certification preparation and certification examination "Quality Officer with TÜV Rheinland certified qualification" (approx. 3 days)

Quality Management – Six Sigma Green Belt

Introduction to Six Sigma (approx. 1 day)

What is Six Sigma? History, Philosophy, and Strategy

DMAIC Project Phases, Objectives, and Roles

Six Sigma in the Context of Lean, Quality Management, and Operational Excellence

Hybrid Project Management with DMAIC for AI Projects


AI-Powered Project Management (approx. 1 day)

Fundamentals of Artificial Intelligence 

Applications Along the DMAIC Framework, Limitations, and Risks

Data and Prompt Fundamentals, Context, and Quality Criteria

Governance, Security, the EU AI Act, and the GDPR

AI Dashboard, Information Consolidation, and Quality Gates


Define – Define (approx. 3 days)

Project identification, strategic relevance, and key metric driver tree

Distinction from CIP and PUL (Problem, Cause, and Solution)

Project Profile: Problem Description and SMART Goal Definition

In-scope and out-scope definitions, as well as AI-supported completeness check

LIPOK and Voice of the Customer (VoC)

Affinity Diagram and Kano Model

VoC-to-CTQ transformation, specifications, and acceptance criteria

AI-supported analysis and technical validation of customer requirements

Cost-effectiveness: ROI, TCO, and qualitative benefits

Stakeholder Analysis and AI-Supported Project Planning

Risk Analysis and Preventive Measures

Change management and motivation for change

Communication strategy, elevator pitch, and AI-supported change story

Quality Gate Review: Define


Measure – Measurement (approx. 3.5 days)

Mathematical process model and cause-and-effect chain of the CTQs

Influence analysis using Ishikawa and KSR, as well as an AI-supported metrics matrix

Data Types and Measurement Scales

Operational definition, data collection methods, and sampling strategy

Data collection plan and control using an AI dashboard

Measurement system analysis: bias, repeatability, reproducibility, and gage R&R

Data quality, plausibility checks, and AI-supported data cleaning

Data Visualization, Statistical Metrics, and Machine and Process Capability

AI-Supported Interpretation of Measurement Results and Quality Gate Review Measure


Analyze – Analysis (approx. 3.5 days)

Process Map and Data Map, as well as Value Stream Analysis

Value stream analysis, spaghetti diagram, TIMWOODS, and Makigami

Distinguishing Between Symptoms, Problems, and Causes

Cause-and-effect and Pareto analysis, as well as AI-supported error code clustering

Hypothesis Formulation and AI as a Sparring Partner

Design of Experiments and AI-assisted testing of influencing factors

Correlation and regression analysis, as well as statistical hypothesis testing and group comparisons

AI-Supported Evidence Matrix and FMEA

Quality Gate Review and Analysis


Improve – Innovative Improvement (approx. 3 days)

Creativity Techniques and AI-Supported Solution Development

Lean solution principles as well as technical and organizational measures

Solution approaches using generative AI, automation, and robotics

Regulatory and organizational requirements for AI deployment

AI-specific risk assessment, as well as feasibility and maturity analyses

Solution evaluation

Acceptance and cost-benefit analysis

Implementation plan and pilot program with success and acceptance criteria

Iterative Approach to AI Pilots and Quality Gate Review Improve


Control – Controlling and Sustainable Implementation (approx. 2 days)

Go-Live, Process Stabilization, and Support During the Start-up Phase

Standard Operating Procedures and Controlling Plan

KPIs, statistical process control, control charts, and corrective actions

Balanced Scorecard and AI-Supported Monitoring

Audit Concept

Project completion, handover, and AI-supported documentation

Quality Gate Review Control


Project work, exam preparation, and final exam (approx. 3 days)

GMP - Good Manufacturing Practice

Introduction to GMP (approx. 2 days)

EU GMP guidelines, AMG, AMWHV

Authorities, drug approvals, marketing authorization

Key persons

FDA, CFR 21

International regulations

AI in the pharmaceutical environment


SOP system (approx. 2.5 days)

Requirements for SOPs

Structure of SOPs

Document control and version management


Training system (approx. 1.5 days)

Employee qualification

Training planning and documentation

Effectiveness control


Deviation and CAPA management (approx. 2 days)

Deviations and CAPA

Requirements for deviation and CAPA management

Documentation of deviations

Error cause analysis

Corrective and preventive measures

CAPA process

AI-supported data analysis for root cause identification


Change management (change control) (approx. 1 day)

Requirements for change management

Notifiable changes, classification of changes

Risk management in the change process

Change management process


Validation and qualification (approx. 1.5 days)

Device, system and room qualification

Process, cleaning and method validation

Qualification and validation process

Qualification and validation documentation


Quality control (approx. 1 day)

Sampling and testing

stability

Dealing with OOS

Storage status

AI-supported evaluation of test data


Complaints management (approx. 0.5 days)

Complaints

Product recall


Audit management (approx. 0.5 days)

Audit types and audit process

Internal audit and FDA inspection

AI-supported data analysis for audit preparation


Supplier qualification (approx. 0.5 days)

Supplier qualification and evaluation


Review and trending (approx. 0.5 days)

Batch Record Review

Product Quality Review

Management Review


Industrial hygiene in the pharmaceutical industry (approx. 2 days)

Personnel hygiene

Hygiene requirements

Clothing and behavior

Production hygiene

Contamination prevention

Hygiene plans


Documentation (approx. 0.5 days)

GMP documentation and data integrity

AI-supported support for document review


Production rooms - clean rooms (approx. 1 day)

General requirements for production rooms

Requirements for premises including storage areas

Avoidance of cross-contamination


Project work (approx. 3 days)

To consolidate the content learned

Presentation of the project results



Changes are possible, the course content is updated regularly.

Knowledge of quality-related activities is recommended for the course.

Once you have completed the course, you will be able to plan, introduce and maintain a quality management system and monitor its effectiveness. You will also have professional knowledge in the application of DIN EN ISO 9001 and in the planning of internal quality audits.

In addition, after completing the course, you will be able to independently and successfully implement Six Sigma projects in accordance with ISO 13053-1 and the DMAIC framework. You will confidently apply the specific tools and methods of process and data analysis, derive improvements based on data, and consistently use AI as a methodological aid. You will design Quality Gate Reviews based on the DMAIC framework and develop AI-powered dashboards for project management, quality control, and decision support.

Furthermore, you are familiar with the requirements of a GMP system, the applicable regulations and the central processes of pharmaceutical quality management. You will understand the basics of SOP systems, CAPA, change management, audit processes, documentation, quality control, industrial hygiene and cleanroom requirements and be able to classify relevant technical terms with confidence.

The course is aimed at managers and employees who are entrusted with quality management, who are to implement a QM system in practice or who would like to develop in the area of quality management, as well as specialists and managers from production and service companies who are actively involved in the QM system and quality improvement.

Specialists in the field of quality management are in demand from both large and medium-sized companies in industry, trade and the service sector.

Additional GMP knowledge is essential in almost all areas of the production of pharmaceuticals and active ingredients, as well as cosmetics, food and animal feed. Your newly acquired knowledge will open up numerous new opportunities for you in these sectors.

Didactic concept

Your lecturers are highly qualified both professionally and didactically and will teach you from the first to the last day (no self-study system).

You will learn in effective small groups. The courses usually consist of 6 to 25 participants. The general lessons are supplemented by numerous practical exercises in all course modules. The practice phase is an important part of the course, as it is during this time that you process what you have just learned and gain confidence and routine in its application. The final section of the course involves a project, a case study or a final exam.

 

Virtual classroom alfaview®

Lessons take place using modern alfaview® video technology - either from the comfort of your own home or at our premises at Bildungszentrum. The entire course can see each other face-to-face via alfaview®, communicate with each other in lip-sync voice quality and work on joint projects. Of course, you can also see and talk to your connected trainers live at any time and you will be taught by your lecturers in real time for the entire duration of the course. The lessons are not e-learning, but real live face-to-face lessons via video technology.

 

The courses at alfatraining are funded by Agentur für Arbeit and are certified in accordance with the AZAV approval regulation. When submitting a Bildungsgutscheinor Aktivierungs- und Vermittlungsgutschein, the entire course costs are usually covered by your funding body.
Funding is also possible via Europäischen Sozialfonds (ESF), Deutsche Rentenversicherung (DRV) or regional funding programs. As a regular soldier, you have the option of attending further training courses via Berufsförderungsdienst (BFD). Companies can also have their employees qualified via funding from Agentur für Arbeit (Qualifizierungschancengesetz).

We will gladly advise you free of charge.

0800 3456-500 Mon. - Fri. from 8 am to 5 pm
free of charge from all German networks.

Contact

We will gladly advise you free of charge. 0800 3456-500 Mon. - Fri. from 8 am to 5 pm free of charge from all German networks.